February 01, 2015 article Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets Molecular Informatics DOI: 10.1002/minf.201400132 OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 256 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Docking-Informed Machine Learning for Kinome-wide Affinity Prediction 2024 Journal of Chemical Information and Modeling article Computer Science Computational Drug Discovery Methods Open access 8 citations Docking-informed machine learning for kinome wide affinity prediction 2024 ChemRxiv preprint Computer Science Computational Drug Discovery Methods Open access 1 citations 2 results References 0